Myths About Designing with Data

There is a lot of buzz about data-driven design, but very little agreement about what that really means. Even deciding how to define data is difficult for teams with spotty access to data within their organizations, uneven understanding, and little shared language. For any site or app, it's standard practice to have analytics, A/B tests, surveys, intercepts, benchmarks, scores of usability tests, ethnographic studies, and interviews. So what counts as data? And more importantly, what will inform design in a meaningful way? This deck explores 6 myths about data and design.

Big Data • What,
where, when, how • Multi-structured • Collected by machines • Broad • Behaviors & actions of many people • Collected as people do what they do • People are not highly aware of data being collected • Analysis uses statistical methods

Thick Data • How
and why • Description • Collected by people • In-depth • Behaviors, actions, emotions, intentions, motivations of a few • Collected as part of a study • People are highly aware of data being collected • Analysis includes developing codes, summaries, and themes